1. Field of the Technology
The technology presented herein relates to an image inspecting apparatus such as an image inspecting apparatus for determining a quality for an image data output from an image sensor (e.g. CCD (Charge Coupled Device)), an image inspecting method using the image inspecting apparatus, a control program for making a computer to execute a processing procedure implementing the image inspecting method and a computer-readable storage medium stored thereon the control program.
2. Description of the Related Art
Conventionally, an image sensor, such as a CCD array, functioning as an image input apparatus is constructed of a large number of pixels (more than several million pixels) which are arranged in two dimensions by applying a semiconductor manufacturing technique. The image sensor goes through many manufacturing steps until its completion. Various flaws occur in the image sensor as a result from defects in the manufacturing steps.
One such defect is “inconsistencies in display characteristics”. The “inconsistencies in display characteristics” are referred to as a luminance change generated by having a certain amount of area on a display screen. The “inconsistencies in display characteristics” are broadly classified into two “inconsistencies in display characteristics”. One of the above-mentioned categories is “inconsistencies in display characteristics” gently changing over a wide range of an entire display (hereinafter, referred to as “shading”). The other is “inconsistencies in display characteristics” locally changing (hereinafter, referred to as “inconsistencies in luminance characteristics).
The “shading” gradually changes from a center portion to a peripheral portion of an image. Therefore, in many cases, when vied only with the naked eye, it is determined that “inconsistencies in display characteristics” do not exist. On the other hand, the “inconsistencies in luminance characteristics” area local luminance change. Thus, it is determined to be a defect, and is obvious to anyone depending on the size of the “inconsistencies in luminance characteristics” and an amount of change thereof.
Conventionally, in a testing apparatus for testing a quality of an image sensor having such “inconsistencies in luminance characteristics”, the following processes are performed so as to determine a quality for the image sensor.
First, an image data output from an image sensor is captured into a testing apparatus. Filtering, such as an average filtering or a two dimensional median filtering, etc, is performed to obtain noise-removed image data in which noise containing a component relating to “inconsistencies in display characteristics” component is removed from the image data.
Next, a difference between the noise-removed image data and the original output image data is calculated to separate the “inconsistencies in display characteristics” component. The concentration of pixels containing the “inconsistencies in display characteristics” is digitized by using an arbitrary threshold value, and a labeling process is performed on the digitized data. Thereafter, a quality for the “inconsistencies in luminance characteristics” is determined depending on a size of a labeled area.
Herein, the two dimensional median filtering is referred to as a noise removing process where an observing window is constructed of a plurality of pixels arranged in the two dimensional manner with a pixel of interest at its center and a concentration value of the pixel of interest is replaced with the center value of the concentration of pixel contained within the observing window.
The labeling process is referred to as a process where a labeling is performed on a pixel for the digitized image data which exceeds a threshold value and the same label is attached to its adjacent pixel in the case where the adjacent pixel also exceeds the threshold value.
However, with the above-described conventional technique, there is a problem that it takes too much time to perform the noise removing process and the labeling process. When the processing time is shortened, there is a problem that the precision for the labeling process decreases.
In order to solve such problems, in a conventional image information processing apparatus disclosed in, for example, Reference 1, precision maintenance as well as reduction of processing time are realized in a noise removing process by combining a median filtering in a horizontal direction (H) and a median filtering in a vertical direction (V), which are a one dimensional filtering, not a two dimensional median filtering. Furthermore, in the image information processing apparatus disclosed in Reference 1, a unique function is used to improve a determining precision in order to determine a quality of “inconsistencies in luminance characteristics”.
[Reference 1] Japanese Laid-Open Publication No. 09-259281
As described above, since the average filtering or the two dimensional median filtering, etc, is used for the noise removing process, there is a problem that it takes much time for the noise removing process with the conventional technique. Furthermore, since it is necessary to digitize the concentration of pixels containing “inconsistencies in display characteristics” component with an arbitrary threshold value and perform a labeling process on the digitized data in order to determine a quality of “inconsistencies in luminance characteristics”. Therefore, there is a problem that it also takes much time to perform the labeling process. Moreover, there is a problem that the precision for the labeling process decreases when the processing time is shortened.
On the other hand, in the image information processing apparatus of Reference 1, precision maintenance as well as reduction of processing time are achieved by combining one dimensional median filterings and improvement of the determining precision is designed by using the unique function in order to determine a quality of the “inconsistencies in luminance characteristics”. However, the labeling process is performed as conventional Thus, when a large area or a large number of “inconsistencies in luminance characteristics” is found, there is a problem that it takes much time to perform the labeling process.
The example embodiment presented herein solves such conventional problems and is designed to improve the detection precision for “inconsistencies in luminance characteristics” for an image data output from an image sensor regardless of a size of area and the number of the “inconsistencies in luminance characteristics”. The example embodiment provides an image inspecting apparatus capable of determining a quality (evaluation) by accurately and quantitatively detecting the “inconsistencies in luminance characteristics” at a high speed, an image inspecting method using the same, a control program for instructing a computer to perform each processing procedure for the method and a computer-readable storage medium for storing the same.
As described above, since the average filtering or the two dimensional median filtering, etc, is used for the noise removing process, there is a problem that it takes much time for the noise removing process with the conventional technique. Furthermore, since it is necessary to digitize the concentration of pixels containing “inconsistencies in display characteristics” component with an arbitrary threshold value and perform a labeling process on the digitized data in order to determine a quality of “inconsistencies in luminance characteristics”. Therefore, there is a problem that it also takes much time to perform the labeling process. Moreover, there is a problem that the precision for the labeling process decreases when the processing time is shortened.
On the other hand, in the image information processing apparatus of Reference 1, precision maintenance as well as reduction of processing time are achieved by combining one dimensional median filterings and improvement of the determining precision is designed by using the unique function in order to determine a quality of the “inconsistencies in luminance characteristics”. However, the labeling process is performed as conventional. Thus, when a large area or a large number of “inconsistencies in luminance characteristics” is found, there is a problem that it takes much time to perform the labeling process.
The example embodiment solves such conventional problems and is designed to improve the detection precision for “inconsistencies in luminance characteristics” for an image data output from an image sensor regardless of a size of area and the number of the “inconsistencies in luminance characteristics”. The example embodiment provides an image inspecting apparatus capable of determining a quality (evaluation) by accurately and quantitatively detecting the “inconsistencies in luminance characteristics” at a high speed, an image inspecting method using the image inspecting apparatus, a control program for making a computer to execute a processing procedure implementing the image inspecting method and a computer-readable storage medium stored thereon the control program.